The accelerated rate of product development and design complexities offered by Additive Manufacturing (AM) has allowed for innovation in the space industry. However, the surface roughness of parts poses a challenge, as it impacts performance and is tied to design choices. Design tools for traditional manufacturing methods fall short in AM contexts, prompting the need for alternative design processes. This work proposes an experimental approach to design for AM investigation using design artefacts to explore a process-structure-property-performance relationship.

Empowering the Participant Voice (EPV) is an NCATS-funded six-CTSA collaboration to develop, demonstrate, and disseminate a low-cost infrastructure for collecting timely feedback from research participants, fostering trust, and providing data for improving clinical translational research. EPV leverages the validated Research Participant Perception Survey (RPPS) and the popular REDCap electronic data-capture platform. This report describes the development of infrastructure designed to overcome identified institutional barriers to routinely collecting participant feedback using RPPS and demonstration use cases. Sites engaged local stakeholders iteratively, incorporating feedback about anticipated value and potential concerns into project design. The team defined common standards and operations, developed software, and produced a detailed planning and implementation Guide. By May 2023, 2,575 participants diverse in age, race, ethnicity, and sex had responded to approximately 13,850 survey invitations (18.6%); 29% of responses included free-text comments. EPV infrastructure enabled sites to routinely access local and multi-site research participant experience data on an interactive analytics dashboard. The EPV learning collaborative continues to test initiatives to improve survey reach and optimize infrastructure and process. Broad uptake of EPV will expand the evidence base, enable hypothesis generation, and drive research-on-research locally and nationally to enhance the clinical research enterprise.

This paper integrates concepts from philosophy and Zen Buddhism in order to define the implications of an American Zen Master’s sermon about the 2009 financial crisis. It interprets three aspects of his sermon: his critique of modernity, his reflection on the experience of Zen meditation (shikan-taza), and his version of Buddhist ontology (tathāgata-garbha). The paper shows that his sermon is an innovative problematization of what it is to be a modern subject or, still more generally, what it is to exist historically. Each of its three aspects indicates a different, perhaps even opposed, response to this problem. Yet they all suggest new configurations of temporality, historicity, and Being. The paper argues that it is precisely this mobile adjacency to the dominant modernist perspective which makes the Zen Master’s sermon both ethically and intellectually effective. Recruiting him into a Nietzschean lineage, it concludes with a programmatic statement of how work in the human sciences could develop his insights.

The article surveys the significance of the dandy as a central figure in nineteenth-century constructions of masculinity and social class.

Turfgrass managers apply nonselective herbicides to control winter annual weeds during dormancy of warm-season turfgrass. Zoysiagrass subcanopies, however, retain green leaves and stems during winter dormancy, especially in warmer climates. The partially green zoysiagrass often deters the use of nonselective herbicides due to variable injury concerns in transition and southern climatic zones. This study evaluated zoysiagrass response to glyphosate and glufosinate applied at four different growing degree day (GDD)-based application timings during postdormancy transition in different locations, including Blacksburg, VA; Starkville, MS; and Virginia Beach, VA, in 2018 and 2019. GDD was calculated using a 5 C base temperature with accumulation beginning January 1 each year, and targeted application timings were 125, 200, 275, and 350 GDD5C. Zoysiagrass injury response to glyphosate and glufosinate was consistent across a broad growing region from northern Mississippi to coastal Virginia, but it varied by application timing. Glyphosate application at 125 and 200 GDD5C can be used safely for weed control during the postdormancy period of zoysiagrass, while glufosinate caused unacceptable turf injury regardless of application timing. Glyphosate and glufosinate exhibited a stepwise increase to maximum injury with increasing targeted GDD5C application timings. Glyphosate applied at 125 or 200 GDD5C did not injure zoysiagrass above a threshold of 30%, whereas glufosinate caused greater than 30% injury for 28 and 29 d when applied at 125 and 200 GDD5C, respectively. Likewise, glyphosate application at 125 or 200 GDD5C did not affect the zoysiagrass green cover area under the progress curve per day, whereas later applications reduced it. Glyphosate and glufosinate caused greater injury to zoysiagrass when applied at greater cumulative heat units and this was attributed to increasing turfgrass green leaf density, because heat unit accumulation is positively correlated with green leaf density. Accumulated heat unit-based application timing will allow practitioners to apply nonselective herbicides with reduced injury concerns.

Simulation is fundamental to many engineering design processes and powers the field of computational design. Simulation inherently consumes energy resulting in CO2 emissions that impact our environment. While one can source energy from renewable sources and use energy efficient hardware, efforts need to also be made in how we can use simulation in a sustainable manner.

This paper presents a sustainable simulation framework that borrows concepts from web services. The framework makes it easy for engineering firms to adopt and embed sustainable simulation practices thereby removing the burden from the designer tin thinking about how to design sustainably. An illustrative example reveals a 25% reduction in computational effort can be achieved by adopting the framework.

This study examined relationships between foodborne outbreak investigation characteristics, such as the epidemiological methods used, and the success of the investigation, as determined by whether the investigation identified an outbreak agent (i.e. pathogen), food item and contributing factor. This study used data from the Centers for Disease Control and Prevention's (CDC) National Outbreak Reporting System and National Environmental Assessment Reporting System to identify outbreak investigation characteristics associated with outbreak investigation success. We identified investigation characteristics that increase the probability of successful outbreak investigations: a rigorous epidemiology investigation method; a thorough environmental assessment, as measured by number of visits to complete the assessment; and the collection of clinical samples. This research highlights the importance of a comprehensive outbreak investigation, which includes epidemiology, environmental health and laboratory personnel working together to solve the outbreak.

In many complex practical optimization cases, the dominant characteristics of the problem are often not known prior. Therefore, there is a need to develop general solvers as it is not always possible to tailor a specialized approach to each application. The previously developed multilevel selection genetic algorithm (MLSGA) already shows good performance on a range of problems due to its diversity-first approach, which is rare among evolutionary algorithms. To increase the generality of its performance, this paper proposes utilization of multiple distinct evolutionary strategies simultaneously, similarly to algorithm selection, but with coevolutionary mechanisms between the subpopulations. This distinctive approach to coevolution provides less regular communication between subpopulations with competition between collectives rather than individuals. This encourages the collectives to act more independently creating a unique subregional search, leading to the development of coevolutionary MLSGA (cMLSGA). To test this methodology, nine genetic algorithms are selected to generate several variants of cMLSGA, which incorporates these approaches at the individual level. The mechanisms are tested on 100 different functions and benchmarked against the 9 state-of-the-art competitors to evaluate the generality of each approach. The results show that the diversity divergence in the principles of working of the selected coevolutionary approaches is more important than their individual performances. The proposed methodology has the most uniform performance on the divergent problem types, from across the tested state of the art, leading to an algorithm more likely to solve complex problems with limited knowledge about the search space, but is outperformed by more specialized solvers on simpler benchmarking studies.

Background: The Domain-Specific Risk Taking scale (DOSPERT) is a widely used instrument that measures perceived risk and benefit and attitude toward risk for activities in several domains, but does not include medical risks.

Objective: To develop a medical risk domain subscale for DOSPERT.

Methods: Sixteen candidate risk items were developed through expert discussion. We conducted cognitive telephone interviews, an online survey, and a random-digit dialing (RDD) telephone survey to reduce and refine the scale, explore its factor structure, and obtain estimates of reliability.

Participants: Eight patients recruited from UIC medical center waiting rooms participated in 45-60 minute cognitive interviews. Thirty Amazon Mechanical Turk workers completed the online survey. One hundred Chicago-area residents completed the RDD telephone survey.

Results: On the basis of cognitive interviews, we eliminated five items due to poor variance or participant misunderstanding. The online survey suggested that two additional items were negatively correlated with the scale, and we considered them candidates for removal. Factor analysis of the responses in the RDD telephone survey and non-statistical factors led us to recommend a final set of 6 items to represent the medical risk domain. The final set of items included blood donation, kidney donation, daily medication use for allergies, knee replacement surgery, general anesthesia in dentistry, and clinical trial participation. The interitem reliability (Cronbach’s α) of the final set of 6 items ranged from 0.57-0.59 depending on the response task. Older respondents gave lower overall ratings of expected benefit from the activities.

Conclusion: We refined a set of items to measure risk and benefit perceptions for medical activities. Our next step will be to add these items to the complete DOSPERT scale, confirm the scale’s psychometric properties, determine whether medical risks constitute a psychologically distinct domain from other risky activities, and characterize individual differences in medical risk attitudes.

While dislike of opposing parties, that is, affective polarization, is a defining feature of contemporary politics, research on this topic largely centers on the United States. We introduce an approach that analyzes affective polarization between pairs of parties, bridging the US two-party system and multiparty systems in other democracies. Analyzing survey data from twenty Western democracies since the mid-1990s, first, we show that partisans' dislike of out-parties is linked to elite policy disagreements on economic issues and, increasingly over time, also to cultural issues. Secondly, we argue and empirically demonstrate that governing coalition partners in parliamentary democracies display much warmer feelings toward each other than we would expect based on elite policy (dis)agreements. Third, we show that radical right parties are disliked much more intensely than we would expect based on policy disputes and coalition arrangements. These findings highlight the policy-based and institutional underpinnings of affective polarization.

While incidence studies based on hospitalisation counts are commonly used for public health decision-making, no standard methodology to define hospitals' catchment population exists. We conducted a review of all published community-acquired pneumonia studies in England indexed in PubMed and assessed methods for determining denominators when calculating incidence in hospital-based surveillance studies. Denominators primarily were derived from census-based population estimates of local geographic boundaries and none attempted to determine denominators based on actual hospital access patterns in the community. We describe a new approach to accurately define population denominators based on historical patient healthcare utilisation data. This offers benefits over the more established methodologies which are dependent on assumptions regarding healthcare-seeking behaviour. Our new approach may be applicable to a wide range of health conditions and provides a framework to more accurately determine hospital catchment. This should increase the accuracy of disease incidence estimates based on hospitalised events, improving information available for public health decision making and service delivery planning.

Political parties face strategic decisions about whether to campaign on issue-based appeals, pertaining to debates over such issues as economic, immigration, and environmental policies, versus valence-based appeals, emphasizing leadership attributes, such as character (integrity, honesty, and so on), along with performance, that is, the ability to deliver positive outcomes. To better understand these choices, we analyze parties' national election campaign strategies across ten Western European democracies. We argue for, and empirically substantiate, an: our issues versus their valence effect, that is, that parties' self-presentations will be more issue-based than their presentations of opponents; an extremist party issue focus effect, that is, that parties with more extreme ideologies most strongly emphasize issues over valence in their self-presentations; and a prime ministerial valence focus effect, that is, that prime ministerial parties more strongly self-present on valence. These findings have implications for election outcomes and mass–elite linkages.